Helping students to meet their goals when they take on a higher education program is naturally something that is very important to colleges. Whether it is a private college or a community college, giving students the support that they need to stay the distance on their courses is essential, both to the students and to the institute itself. High dropout rates and mediocre grades not only affect the morale of students and staff, but they can also have a very big impact on the reputation of a higher education facility.
The Challenges of Student Retention
Of course, it can be difficult for staff to know when a student is considering dropping out, or when they are experiencing situations or issues in their lives that make committing to studying and keeping up with their course harder. This can be especially difficult with a large student body. In some cases, students who drop out of a course or indefinitely defer it could have been retained if some extra support was offered, however it is not possible for a college to offer that extra support to all of the students, all of the time. They therefore need to be able to identify students who are at risk, and be able to take action to help them.
This is where data is making a huge difference.
Identifying at Risk Students with Analytics
An approach many colleges are now taking is to use technology that can take student data and make predictions about the probable arc of a given student’s experience at college. This is done using advanced data analysis tools, for example the student retention specific software platform Nuro. Tools like these can compare student profiles on enrolment to other similar students and assess what the risk of the student dropping out would be. This gives an insight into which students are at risk from the start of the course, allowing staff to be informed about those who may need extra support.
Identifying Risks That Emerge Through a Program
Naturally, students who appear to be at risk when they enroll may not be in the same situation two years later, and vice versa; students who did not flag any potential risk when they started may encounter situations that threaten their retention and success later in the course. Analytics tools can help here too, by highlighting when any student is deviating from what they would be expected to achieve throughout the course. Factors like attendance and exam results all play a part, and can help indicate a student who is encountering new difficulties and may be in the at-risk category, even where they were not identified as such at enrolment.
Using analysis systems like these can allow staff to have a greater insight into what may help them keep the highest number of the students they have, and help them succeed in graduating. Of course, all analysis can do is predict who may need help – after that, it is down to the real people who make up the college to decide how to provide it!
